对激光多点寻位、焊前轨迹拟合、焊缝实时跟踪的3种结构光视觉辅助焊接的轨迹识别与控制技术进行了研究.提出了适用于上述三者的以CNN模型、自适应特征提取算法、先验模型、坐标矩阵转换为核心的焊接轨迹识别流程.提出了分别对应上述三者的焊接轨迹控制模型：示教轨迹修正模型、焊前轨迹拟合模型、焊缝跟踪实时纠偏模型. 结果表明，激光多点寻位、焊前轨迹拟合模式焊接时，能够在焊前高效地识别出焊接轨迹曲线，焊接轨迹与焊缝中心线基本重合；焊缝实时跟踪模式焊接时，系统能够实时矫正焊枪的偏差.文中提到的焊接轨迹识别流程与轨迹控制模型足以保证结构光视觉辅助焊接的稳定运行.
Three trajectory recognition and control techniques for laser multi-point positioning, pre-welding trajectory fitting, and seam real-time tracking for structured light vision-assisted welding are investigated. A CNN model, adaptive feature extraction algorithm, a priori model, and coordinate matrix conversion are proposed as the core of the welding trajectory recognition process for these three. Welding trajectory control models are proposed for each of the above three, which including a taught trajectory correction model, a pre-welding trajectory fitting model, and a real-time deflection correction model for seam tracking. The experiments prove that laser multi-point positioning, pre-welding trajectory fitting model can efficiently identify the weld trajectory curve before welding, and the welding trajectory basically coincides with the centerline of the seam; when welding in the real-time seam tracking model, the real-time deviation is mainly controlled within ± 0.2 mm, with an average deviation of 0.1160 mm. The results show that the welding trajectory identification process and trajectory control model mentioned in this paper are sufficient to ensure stable operation of structured light vision-assisted welding.
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